Search results for: Mixture Module Gaussian

Authors: A. Alshebani, Y. Swesi, S. Mrayed, F. Altaher, I. Musbah

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Cs-type nanocomposite zeolite membrane was successfully synthesized on an alumina ceramic hollow fibre with a mean outer diameter of 1.7 mm; cesium cationic exchange test was carried out inside test module with mean wall thickness of 230 μm and an average crossing pore size smaller than 0.2 μm. Separation factor of n-butane/H₂ obtained indicate that a relatively high quality closed to 20. Maxwell-Stefan modeling provides an equivalent thickness lower than 1 µm. To compare the difference an application to CO₂/N₂ separation has been achieved, reaching separation factors close to (4,18) before and after cation exchange on H-zeolite membrane formed within the pores of a ceramic alumina substrate.

Keywords: MFI membrane, nanocomposite, Ceramic hollow fibre, CO2, Ion-exchange.

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Authors: Kristina Davoian, Wolfram-M. Lippe

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Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

Keywords: Artificial Neural Networks (ANN), Learning Theory, Evolutionary Programming (EP), Mutation, Self-Adaptation.

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Authors: Mohamed Azab

Abstract:

In this paper a new maximum power point tracking algorithm for photovoltaic arrays is proposed. The algorithm detects the maximum power point of the PV. The computed maximum power is used as a reference value (set point) of the control system. ON/OFF power controller with hysteresis band is used to control the operation of a Buck chopper such that the PV module always operates at its maximum power computed from the MPPT algorithm. The major difference between the proposed algorithm and other techniques is that the proposed algorithm is used to control directly the power drawn from the PV. The proposed MPPT has several advantages: simplicity, high convergence speed, and independent on PV array characteristics. The algorithm is tested under various operating conditions. The obtained results have proven that the MPP is tracked even under sudden change of irradiation level.

Keywords: Photovoltaic, maximum power point tracking, MPPT.

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Authors: B. Bagheri Nakhjavanlo, T. J. Ellis, P. Raoofi, J. Dehmeshki

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This paper presents a customized deformable model for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic aneurysm is the need to overcome problems associated with intensity inhomogeneities and image noise. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A Gaussian kernel function in the level set formulation, which extracts the local intensity information, aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets. The results indicate the method is more effective than other approaches in coping with intensity inhomogeneities.

Keywords: Abdominal and thoracic aortic aneurysms, intensityinhomogeneity, level sets, local fitting binary.

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Authors: Emilio Delgado, William Aperador, Alis Pataquiva

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Biomass is becoming a large renewable resource for power generation; it is involved in higher frequency in environmentally clean processes, and even it is used for biofuels preparation. On the other hand, hydrogen – other energy source – can be produced in a variety of methods including gasification of biomass. In this study, the production of hydrogen by gasification of biomass waste is examined. This work explores the production of a gaseous mixture with high power potential from Amazonas´ specie known as copoazu, using a counter-flow fixed-bed bioreactor.

Keywords: Copoazu, Gasification, Hydrogen production.

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Authors: S. Grace Sahaya Sheba, R. Omegala Priakumari

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Polyethylene glycol (PEG) is a condensation polymer of ethylene oxide and water. It is soluble in water and in many organic solvents. PEG is used to make emulsifying agents, detergents, soaps, plasticizers, ointments etc. Ethanol (C₂H₅OH) also known as ethyl alcohol is a well-known organic compound and has wide applications in chemical industry as it is used as a solvent for paint, varnish, in preserving biological specimens, used as a fuel mixed with petrol etc. Though their chemical and physical properties are already studied, still because of their uses in day to day life the authors thought it is better to study some more of their physical properties like ultrasonic velocity and hence adiabatic compressibility, free length, etc. A detailed study of such properties and some excess parameters like excess adiabatic compressibility, excess free volume and few more in the liquid mixtures of these two compounds with PEG as a solute and Ethanol as a solvent at various mole fractions may throw some light on deeper understanding of molecular interaction between the solute and the solvent supported by NMR, IR etc. Hence the present research work is on ultrasonics/allied studies on these two liquid mixtures. Ultrasonic velocity (U), density (ρ) and viscosity (η) at room temperature and at different mole fraction from 0 to 0.055 of ethanol in PEG have been experimentally carried out by the authors. Acoustical parameters such as adiabatic compressibility (β), free volume (V_f), acoustic impedance (Z), internal pressure (π_i), intermolecular free length (L_f) and relaxation time (τ) were calculated from the experimental data. We have calculated excess parameters like excess adiabatic compressibility (β^E), excess internal pressure (π_i^E) free length (L_f^E) and excess acoustic impedance (Z^E) etc for these two chosen liquid mixtures. The excess compressibility is positive and maximum around a mole fraction 0.007 and excess internal pressure is negative and maximum at the same mole fraction and longer free length. The results are analyzed and it may be concluded that the molecular interactions between the solute and the solvent is not strong and it may be weak. Appropriate graphs are drawn.

Keywords: Adiabatic Compressibility, Binary mixture, Induce dipole, Polarizability, Ultrasonic.

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Authors: Mohammad Shams Esfand Abadi, John Hakon Husøy

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Employing a recently introduced unified adaptive filter theory, we show how the performance of a large number of important adaptive filter algorithms can be predicted within a general framework in nonstationary environment. This approach is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. This general performance analysis can be used to evaluate the mean square performance of the Least Mean Square (LMS) algorithm, its normalized version (NLMS), the family of Affine Projection Algorithms (APA), the Recursive Least Squares (RLS), the Data-Reusing LMS (DR-LMS), its normalized version (NDR-LMS), the Block Least Mean Squares (BLMS), the Block Normalized LMS (BNLMS), the Transform Domain Adaptive Filters (TDAF) and the Subband Adaptive Filters (SAF) in nonstationary environment. Also, we establish the general expressions for the steady-state excess mean square in this environment for all these adaptive algorithms. Finally, we demonstrate through simulations that these results are useful in predicting the adaptive filter performance.

Keywords: Adaptive filter, general framework, energy conservation, mean-square performance, nonstationary environment.

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Authors: L. Dzierzbicka-Głowacka, M. Janecki

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Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Keywords: Ecosystem model, phytoplankton, Baltic Sea

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Authors: Ankit R Patel, Ankit A Patel, Mahesh A Patel, Dhaval R Vyas

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Although lighting systems powered by Photovoltaic (PV) cells have existed for many years, they are not widely used, especially in lighting for buildings, due to their high initial cost and low conversion efficiency. One of the technical challenges facing PV powered lighting systems has been how to use dc power generated by the PV module to energize common light sources that are designed to operate efficiently under ac power. Usually, the efficiency of the dc light sources is very poor compared to ac light sources. Rapid developments in LED lighting systems have made this technology a potential candidate for PV powered lighting systems. This study analyzed the efficiency of each component of PV powered lighting systems to identify optimum system configurations for different applications.

Keywords: Energy Efficiency, LED, Modeling of systems, Photovoltaic.

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Authors: Mohammed Zidane, Said Safi, Mohamed Sabri, Ahmed Boumezzough

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In this paper we propose an algorithm based on higher order cumulants, for blind impulse response identification of frequency radio channels and downlink (MC−CDMA) system Equalization. In order to test its efficiency, we have compared with another algorithm proposed in the literature, for that we considered on theoretical channel as the Proakis’s ‘B’ channel and practical frequency selective fading channel, called Broadband Radio Access Network (BRAN C), normalized for (MC−CDMA) systems, excited by non-Gaussian sequences. In the part of (MC−CDMA), we use the Minimum Mean Square Error (MMSE) equalizer after the channel identification to correct the channel’s distortion. The simulation results, in noisy environment and for different signal to noise ratio (SNR), are presented to illustrate the accuracy of the proposed algorithm.

Keywords: Blind identification and equalization, Higher Order Cumulants, (MC−CDMA) system, MMSE equalizer.

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Authors: Adel Aloraini

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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Ghobad Gorji, Hasan Golabi

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The goal of this paper is to describe the design of an ultra-wideband (UWB) system that is optimized for the low-rate wireless personal area network application. To this aim, we propose a system based on direct chaotic communication (DCC) technology. Based on this system, a 2-GHz wide chaotic signal is produced into the UWB spectrum lower band, i.e., 3.1–5.1 GHz. For this system, two simple modulation schemes, namely chaotic on-off keying (COOK) and differential chaos shift keying  (DCSK) are evaluated first. We propose a modulation scheme, namely Double DCSK, to improve the performance of UWB DCC. Different characteristics of these systems, with Monte Carlo simulations based on the Additive White Gaussian Noise (AWGN) and the IEEE 802.15.4a standard channel models, are compared.

Keywords: Ultra-wideband, UWB, Direct Chaotic Communication, DCC, IEEE 802.15.4a, COOK, DCSK.

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Authors: Said C. Fares, Mary A. Fares

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It is well documented that introductory computer programming courses are difficult and that failure rates are high. The aim of this project was to reduce the high failure and withdrawal rates in learning to program. This paper presents a number of changes in module organization and instructional delivery system in teaching CS1. Daily out of class help sessions and tutoring services were applied, interactive lectures and laboratories, online resources, and timely feedback were introduced. Five years of data of 563 students in 21 sections was collected and analyzed. The primary results show that the failure and withdrawal rates were cut by more than half. Student surveys indicate a positive evaluation of the modified instructional approach, overall satisfaction with the course and consequently, higher success and retention rates.

Keywords: Failure Rate, Interactive Learning, Student engagement, CS1.

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Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

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Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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Authors: M. A. M. El-Bendary, A. E. Abu El-Azm, N. A. El-Fishawy, F. Shawky, F. E. El-Samie

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With increasing utilization of the wireless devices in different fields such as medical devices and industrial fields, the paper presents a method for simplify the Bluetooth packets with throughput enhancing. The paper studies a vital issue in wireless communications, which is the throughput of data over wireless networks. In fact, the Bluetooth and ZigBee are a Wireless Personal Area Network (WPAN). With taking these two systems competition consideration, the paper proposes different schemes for improve the throughput of Bluetooth network over a reliable channel. The proposition depends on the Channel Quality Driven Data Rate (CQDDR) rules, which determines the suitable packet in the transmission process according to the channel conditions. The proposed packet is studied over additive White Gaussian Noise (AWGN) and fading channels. The Experimental results reveal the capability of extension of the PL length by 8, 16, 24 bytes for classic and EDR packets, respectively. Also, the proposed method is suitable for the low throughput Bluetooth.

Keywords: Bluetooth, throughput, adaptive packets, EDRpackets, CQDDR, low latency. Channel condition

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: AlexNet, Deep learning, image recognition, 6D posture estimation.

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Authors: Karel Borovec, Jerzy Gorecki, Tadeas Ochodek

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Combustion of solid fuels is one of the main sources of mercury in the environment. To reduce the amount of mercury emitted to the atmosphere, it is necessary to modify or optimize old purification technologies or introduce the new ones. Effective reduction of mercury level in the flue gas requires the use of speciation systems for mercury form determination. This paper describes tests and provides comparison of two industrial portable and continuous systems for mercury speciation in the flue gas: Durag HM-1400 TRX with a speciation module and the Portable Continuous Mercury Speciation System based on the SGM-8 mercury speciation set, made by Nippon Instruments Corporation. Additionally, the paper describes a few analytical problems that were encountered during a two-year period of using the systems.

Keywords: Mercury determination, speciation, continuous measurement, flue gas.

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Authors: Alireza BozorgianÏî Navid Majdi Nasab, Hassan Mirzazadeh

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In this paper, the effect of modified clay on the mechanical efficiency of epoxy resin is examined. Studies by X ray diffraction and microscopic transient electron method show that modified clay distribution in polymer area is intercalated kind. Examination the results of mechanical tests shows that existence of modified clay in epoxy area increases pressure yield strength, tension module and nano composite fracture toughness in relate of pure epoxy. By microscopic examinations it is recognized too that the action of toughness growth of this kind of nano composite is due to crack deflection, formation of new surfaces and fracture of clay piles.

Keywords: Nano clay, Epoxy, Toughness, Composite

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Othman Belgassim, Krzysztof Jemielniak

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The analysis of Acoustic Emission (AE) signal generated from metal cutting processes has often approached statistically. This is due to the stochastic nature of the emission signal as a result of factors effecting the signal from its generation through transmission and sensing. Different techniques are applied in this manner, each of which is suitable for certain processes. In metal cutting where the emission generated by the deformation process is rather continuous, an appropriate method for analysing the AE signal based on the root mean square (RMS) of the signal is often used and is suitable for use with the conventional signal processing systems. The aim of this paper is to set a strategy in tool failure detection in turning processes via the statistic analysis of the AE generated from the cutting zone. The strategy is based on the investigation of the distribution moments of the AE signal at predetermined sampling. The skews and kurtosis of these distributions are the key elements in the detection. A normal (Gaussian) distribution has first been suggested then this was eliminated due to insufficiency. The so called Beta distribution was then considered, this has been used with an assumed β density function and has given promising results with regard to chipping and tool breakage detection.

Keywords: AE signal, skew, kurtosis, tool failure

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection.

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Authors: Ivan Stanev, Maria Koleva

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Common Platform for Automated Programming (CPAP) is defined in details. Two versions of CPAP are described: Cloud based (including set of components for classic programming, and set of components for combined programming); and Knowledge Based Automated Software Engineering (KBASE) based (including set of components for automated programming, and set of components for ontology programming). Four KBASE products (Module for Automated Programming of Robots, Intelligent Product Manual, Intelligent Document Display, and Intelligent Form Generator) are analyzed and CPAP contributions to automated programming are presented.

Keywords: Automated Programming, Cloud Computing, Knowledge Based Software Engineering, Service Oriented Architecture.

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Authors: Mohammed Nasir Kajama, Ngozi Claribelle Nwogu, Edward Gobina

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Pt/γ-Al2O3 membrane catalysts were prepared via an evaporative-crystallization deposition method. The obtained Pt/γ- Al2O3 catalyst activity was tested after characterization (SEM-EDAX observation, BET measurement, permeability assessment) in the catalytic oxidation of selected volatile organic compound (VOC) i.e. propane, fed in mixture of oxygen. The VOC conversion (nearly 90%) obtained by varying the operating temperature showed that flow-through membrane reactor might do better in the abatement of VOCs.

Keywords: VOC combustion, flow-through membrane reactor, platinum supported alumina catalysts.

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Authors: Dengpan Wu, Dan Liu

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In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization system mechanism of super calls and grant table, based on the virtual machine manager internal implementation of access control module (ACM) to design the security isolation system memory. Experiments show that, the system can effectively isolate different customer domain OS between illegal access to memory data.

Keywords: Cloud security, memory isolation, Xen, virtual machine.

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Authors: Basem Mustafa Abd. Amer , Syed Abdul Rahman Al-Attas

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The aim of this research is to develop a fast and reliable surveillance system based on a personal digital assistant (PDA) device. This is to extend the capability of the device to detect moving objects which is already available in personal computers. Secondly, to compare the performance between Background subtraction (BS) and Temporal Frame Differencing (TFD) techniques for PDA platform as to which is more suitable. In order to reduce noise and to prepare frames for the moving object detection part, each frame is first converted to a gray-scale representation and then smoothed using a Gaussian low pass filter. Two moving object detection schemes i.e., BS and TFD have been analyzed. The background frame is updated by using Infinite Impulse Response (IIR) filter so that the background frame is adapted to the varying illuminate conditions and geometry settings. In order to reduce the effect of noise pixels resulting from frame differencing morphological filters erosion and dilation are applied. In this research, it has been found that TFD technique is more suitable for motion detection purpose than the BS in term of speed. On average TFD is approximately 170 ms faster than the BS technique

Keywords: Surveillance, PDA, Motion Detection, ImageProcessing , Background Subtraction.

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Authors: Erika J. Ruíz, Jairo R. Cortes, Willian A. Aperador

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In this article was evaluated the protective effect of the alternative concrete obtained from the binary mixture of fly ash, and iron and steel slag. After mixing the cement with aggregates, structural steel was inserted in the matrix cementitious. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The chloride ion effect on the specimens accelerated under controlled conditions (3.5% NaCl and 25°C temperature). The impedance data were acquired in a range of 1 mHz to 100 kHz.

Keywords: Alternative concrete, corrosion, alkaline activation.

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Authors: Conradie, P.W., Lombard, A., Moller, M.

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The dramatic effect of information technology on society is undeniable. In education, it is evident in the use of terms like active learning, blended learning, electronic learning and mobile learning (ubiquitous learning). This study explores the perceptions of 54 learners in a higher education institution regarding the use of mobile devices in a third year module. Using semi-structured interviews, it was found that mobile devices had a positive impact on learner motivation, engagement and enjoyment. It also improved the consistency of learning material, and the convenience and flexibility (anywhere, anytime) of learning. User-interfacelimitation, bandwidth and cognitive overload, however, were of concern. The use of cloud based resources like Youtube and Google Docs, through mobile devices, positively influenced learner perceptions, making them prosumers (both consumers and producers) of education content.

Keywords: Active learning, education, mobile learning, pedagogy.

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Authors: Tomoya Okubo, Kuninori Nakamura, Shin-ichi Mayekawa

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In this research, a latent class vector model for pairwise data is formulated. As compared to the basic vector model, this model yields consistent estimates of the parameters since the number of parameters to be estimated does not increase with the number of subjects. The result of the analysis reveals that the model was stable and could classify each subject to the latent classes representing the typical scales used by these subjects.

Keywords: finite mixture models, latent class analysis, Thrustone's paired comparison method, vector model

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: Biometrics, finger vein recognition, Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA).

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Authors: Stephen Karungaru, Minoru Fukumi, Norio Akamatsu

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In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.

Keywords: color transition, genetic algorithms morphing, warping

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